The tone mapping problem relates to tone reproduction of high dynamic range (HDR) content on low dynamic range (LDR) displays. In most applications, the tone mapping process must usually meet two requirements: keep image details, e.g. local contrast; and maintain the appearance of relative brightness. Current known work on tone mapping focuses on the first requirement and simply neglects the second one, which is usually the most important from the artists' perspective. Additionally, the currently available tone mapping algorithms do not allow manipulating the tone of different parts of the picture and thus often fail to match the sensation of the original HDR content.
High dynamic range (HDR) has received much attention in recent years as an alternative format for digital imaging. The traditional Low Dynamic Range (LDR) image format was designed for displays compliant with ITU-R Recommendation BT 709 (a.k.a. Rec. 709), where only two orders of magnitude of dynamic range can be achieved. Real world scenes, however, have a much higher dynamic range, around ten orders of magnitude in daytime, and the human visual system (HVS) is capable of perceiving 5 orders of magnitude at the same time.
The amount of visual content available in HDR format is increasing: the latest advances in digital sensors and film stock allows content creators to capture images with very high dynamic range, and computer generated graphics (e.g. animation films, visual effects and games) allow creating visual content with virtually unlimited dynamic range. HDR displays, however, are not mainstream devices yet; a few HDR display devices are already available as prototypes and top-of-the-line HDTVs, but the number of such displays is still very small compared to the widely used LDR displays.
In order to display an HDR image on a LDR display device, a tone mapping method is employed to map the HDR image, which is usually available as radiance, to 8 bit RGB index numbers. The tone mapping process is not obvious because it has to simulate the process that happens in the HVS so that the tone mapped LDR image can deceive the HVS into believing it is close enough to the original HDR image. This requires the tone mapping algorithm to be able to maintain both the local contrast and the perceptual brightness.
Tone mapping for HDR image has been studied in recent years in computer graphics as well as in image/video processing communities. Roughly speaking, tone mapping methods can be classified into two primary categories: global tone mapping and local tone mapping.
Global tone mapping uses a global curve to map radiance to image intensity. Although it has the advantages such as low complexity and easy manual control, it is not able to keep all the details when it comes to considerably high dynamic range. Therefore, global tone mapping is not suitable for applications that require very high quality output (like post-production).
Local tone mapping methods, on the other hand, offer a higher quality result by compressing each individual pixel according to local image characteristics. In particular, these methods try to simulate the visual adaptation that happens in the HVS, but in practice most of them do not mimic the behavior of the HVS explicitly. Instead, they make simple assumptions about the HVS and then try to compress the dynamic range of the image using these assumptions to get a visually good-looking result. Even if with careful fine-tuning of the local tone mapping method it is possible to generate convincing results for a relatively wide range of HDR images, the understanding of visual adaptation is still far from complete. Therefore, there is no algorithm that behaves like the human eye. Additionally, these methods do not offer good manual control of the tone mapping process, severely limiting the creativity typically involved in tone correction processing.
Tone mapping is not only studied by image processing researchers, but also by painters as well as film photographers. They face the same problem of using a limited dynamic range media (i.e. canvas for painters and print paper for photographers) to represent the high dynamic range scenes. Referring to FIG. 1, here we review the “Zone System” 100, which is a photographic technique formulated by Ansel Adams and Fred Archer. The Zone System assigns numbers from 0 through 10 to different perceptual brightness, with 0 representing black, 5 middle gray, and 10 pure white. These values are known as zones. In the theory of the Zone System, a photographer first identifies the key elements in the scene and places these elements on the desired zones.
This process relies on the perception of the scene rather than the measurement of the radiance. Then a light meter is used to measure the radiance for each key element in the scene. As there can be only a single exposure value per shot, an exposure value is chosen such that the most important element is mapped to the desired zone. As a result, other (also important) elements may be mapped to the “wrong” zone, becoming either too dark or too bright. Afterwards, in the printing process, this problem is fixed by applying a “dodge and burn” operation, which is a printing technique where some light is withheld from a portion of the print during development (dodge), or more light is added to that region (burn). Therefore, a key element that is mapped to a lower zone than the desired one will be exposed in the light longer than the rest part of the picture. Similarly, the key element that is mapped to a higher zone than the desired one will be exposed less. This local processing will guarantee that the key elements of the picture are mapped to the desired zone in the final output. In other words, the perceptual brightness of these key elements remains consistent with how they look like in real life.
This approach can be used with digital images, but there is no method with good performance in automatic mode that at the same time provides intuitive control in a user-assisted mode.